Using AI for my
AI Community:

A Journey from Digital Native to AI Immigrant

Written by:

Huang Yi Jen

Senior Consultant
Sapience Consulting

Marc Prensky coined the terms ‘digital native’ and ‘digital immigrant’ – the former is the generation that grew up in the digital age, predominantly regarding individuals born from 1980 onwards, namely Millennials, Generation Z, and Generation Alpha. Individuals from these demographic cohorts can quickly and comfortably locate, consume and send digital information through electronic devices and platforms such as computers, mobile phones, and social media. The latter is people who grew up in a world dominated by print and television, born before the advent of the Internet.

However, as time goes by, ‘Digital Natives’ are now ‘AI immigrants.’ Regardless, let’s try to have some AI insight on everything we are doing. For good? or for bad? We shall see and be open-minded.

I imagine some of you have been bombarded with my (almost) daily AI posts for the past 6 months. Various Sapience communities have been launched since, e.g. GRC, project management, cybersecurity, Privacy, etc.

I am using this opportunity to ask Gemini and ChatGPT to provide some feedback, reflect on the experience, and potentially to ‘improve’ (or change at least) my approach.

Category	Gemini’s Analysis	GPT-4o’s Analysis	My Own Notes
Post Count How many posts are there in the file?	55	109	Actual count: 103
Categorisation Strategy Please categorise all posts into 5 groups	Sectors: Infrastructure, Business, Tech, Public Life, Sports.	Functional: Research, Strategy, Products, Ethics, Media.	Both did a “pretty good” job.
The “Best” Post Which one is the best post? and why?	Mistral AI (20251204): Highlighted the shift to “small models” and Singapore’s Home Team collaboration.	Meta & Scale AI (20250730): Highlighted the $14B investment in data as the “oxygen” for AI.	Good, both identified high-signal, real-world impact posts.
The “Boring” Post Which is the most boring one? and why?	LLM Linguistics (20250919): Research on words like “delve” and “meticulous.”	Link Only (20251125): A simple link to Anthropic with no added context.	GPT caught the lack of signal; Gemini caught the irony of AI-speak.
Source Inference Could you tell how I came across the content?	Identified News Aggregators and Financial Media as primary pipelines.	Identified Tech Media (FT, BBC) and Research Blogs (Anthropic, Google).	Both were “close enough.”
Bias/Preferences Do my posts infer any political views or cultural preferences?	Inferred preferences for Western Tech, Open Systems, and Regulation	No political stance or strong cultural preference inferred.	An interesting look at how different models “perceive” bias.
Media Sources Please recommend a media source that I can use for the next posts.	Daily Newsletters (Ben’s Bites) or MIT Technology Review.	Semafor – Semafor Tech (and Semafor AI).	Good, all recommendations are high-quality.
Virality Potential How likely my posts would become viral?	Low: Cited the nature of a consistent news digest as anti-viral.	Low (Current): High-signal but needs structural changes to “pop” on feeds.	Very honest feedback.
Actionable Advice Please give me 2 actionable concise ideas to improve the posts	Add a “So What?”/”Key Takeaway” summary & tagging system.	Add a one-line takeaway & group posts with consistent micro-tags.	Both suggested nearly the same thing.

After asking questions 1 to 6 to reflect my posts, I understand more why my friend complained that his wife took AI’s advice more seriously than his and why people ask AI about sensitive / confidential questions (instead of seeking real human help – not even professional help). However, the importance of ‘human in the loop’ is so easily neglected. The extra precaution to verify the responses is so crucial.

The responses to questions 7-9 do provide genuine ideas for me to kick start; however, if I were to simply follow accordingly, the approach would take away the fun part of how I have been doing the posts – I listen to news podcasts from various sources and enjoy being inspired or intrigued. Potentially, turning the posts into a daily chore for me, e.g. reposting of some reposts.

Being a consultant, when customers compliment that I ask the right or good questions, I think that’s the most important early sign of good project engagement. Interestingly, the ability to ask good questions, a.k.a. prompt engineering or context engineering, also plays such an important role in the world of AI.

Last week, 2 attendees of my CISSP class vividly and passionately traded NAS (network attached storage) building tricks and tips. I was super impressed by the extent of using technology outside of work by them, including configuring guest vLAN, segregating security zones, setting up firewalls etc. As we progress in career and life, passion is a key driver for continuous learning. When I can turn work into a fun activity, it is no longer a chore.

You could join the community to see how my posts evolve!